Computer implemented method for performing cloud computing on data being stored pseudonymously in a database

ABSTRACT

The invention relates to a computer implemented method for performing cloud computing on data of a first user employing cloud components, the cloud components comprising a first database and a data processing component, wherein an asymmetric cryptographic key pair is associated with the first user, said asymmetric cryptographic key pair comprising a public key and a private key, the data being stored pseudonymously non-encrypted in the first database with the data being assigned to an identifier, wherein the identifier comprises the public key, the method comprising retrieving the data from the first database by the data processing component, wherein retrieving the data from the first database comprises receiving the identifier and retrieving the data assigned to the identifier from the first database, wherein the method further comprises processing the retrieved data by the data processing component and providing a result of the analysis.

RELATED APPLICATIONS

This application claims the priority of:

-   1. European Application Number: EP10 194 681.2, filed Dec. 13, 2010; -   2. European Application Number: EP10 173 198.2, filed Aug. 18, 2010; -   3. European Application Number: EP10 173 175.0, filed Aug. 18, 2010; -   4. European Application Number: EP10 173 163.6, filed Aug. 18, 2010; -   5. European Application Number: EP10 167 641.9, filed Jun. 29, 2010; -   6. European Application Number: EP10 156 171.0, filed Mar. 11, 2010;     and -   7. European Application Number: EP09 179 974.2, filed Dec. 18, 2009.

FIELD OF THE INVENTION

The present invention relates to the field of computer implemented identifier generators.

BACKGROUND AND RELATED ART

Cloud computing is well known in the art and describes distributed computing in a large network, like the internet, wherein shared resources, software, and information are provided to computers and other devices on demand. One popular example for cloud computing is the usage of web-based applications which can be accessed and used on demand trough for example web interfaces of personal computers.

A problem that arises in cloud computing is that data on which cloud computing has to be performed has to be provided to respective cloud components like hardware or software components distributed within the cloud. However, in case the data comprises personal information of individual cloud users or any kind of sensitive information, it is desired to ensure that the information is stored in a way that it is not possible to analyze the data in order to draw conclusions on the personal identity of the users.

SUMMARY

The invention provides a computer implemented method, a computer program product and a computing device in the independent claims. Embodiments are given in the dependent claims.

The invention provides a computer implemented method for performing cloud computing on data of a first user employing cloud components, the cloud components comprising a first database and a data processing component, wherein an asymmetric cryptographic key pair is associated with the first user, said asymmetric cryptographic key pair comprising a public key and a private key, the data being stored pseudonymously and non-encrypted in the first database with the data being assigned to an identifier, wherein the identifier comprises the public key, the method comprising retrieving the data from the first database by the data processing component, wherein retrieving the data from the first database comprises receiving the identifier and retrieving the data assigned to the identifier from the first database, wherein the method further comprises processing the retrieved data by the data processing component and providing a result of the analysis.

The term ‘identifier’ as used herein may be a reference used for identifying or locating data in the database. For example, in some embodiments an identifier may be a pseudonym. The pseudonym allows identification of the assignment of various records. In other embodiments the identifier may identify a record or records within the database. Records may be individual data files or they may be a collection of data files or tuples in a database relation. An identifier may be an access key like a primary key for a relation in a database. An identifier may also be a unique key for a relation in a relational database.

Embodiments of the invention have the advantage that even though personal data of a user is stored in a database in an unencrypted manner, analyzing the data of the user only provides a result of the analysis which does not permit to draw any conclusions about the user's identity. The only identifier which assigns the data to the user comprises a public key of the first user, which appears as a random value and thus does not allow to draw any conclusions about the first user's identity. Thus, cloud computing can be performed while ensuring a high user anonymity in the cloud.

In accordance with an embodiment of the invention, the cloud components further comprise a second database, wherein initially the data is only stored encrypted with the aforementioned first user's public key in the second database, wherein the method further comprises retrieving the data from the second database and storing the unencrypted data pseudonymously in the first database assigned to the identifier, wherein after said storage of the data in the first database the data is retrieved from the first database by the data processing component, wherein the data processing is only performed on said data retrieved from the first database.

This has the advantage, that the real data processing can be performed on non-encrypted data by a clear text processing site, wherein permanent data storage is performed in an encrypted manner. Thus, the data is only temporally required to be stored non-encrypted in the first database for the real data processing procedure. Consequently, this permits to use clear text processing sites with personal data—a user may decide by himself if he trusts a certain clear text processing site, in turn decrypts his data, stores his decrypted data pseudonymously in the first database and provides the clear text processing site with the respective identifier. Nevertheless, absolute anonymity in data processing is ensured since the identifier comprising the user's public key does not allow to draw any conclusions on the personal identity of the first user.

In accordance with a further embodiment of the invention, the method further comprises storing a result of the data processing step in the first database assigned to the identifier. Then, the user may retrieve the result of the data from the first database and store said retrieved data encrypted with his public keys in the second database. Finally, it may be preferred that the result of the data is deleted from the first database. Also, it may be preferred that the data being stored pseudonymously and non-encrypted in the first database with the data being assigned to an identifier will be deleted after a final data processing step on said data.

This has the advantage that the first database can be kept as a temporary storage space while all relevant user data and respective data analysis on said user data is stored together in the second database in a highly secure manner.

Preferably, the first user has a private key, from which a whole set of public keys is calculated, wherein the private key and each public key of the set of public keys form an asymmetric cryptographic key pair. Then, the first user's data is stored pseudonymously in the first database with the data being assigned to an identifier, wherein the identifier comprises one of the public keys. With an increasing number of public keys generated from a single private key and the data being stored pseudonymously in the first database with the data being assigned to an identifier, each identifier comprising a different one of said user's public keys, personal anonymity is further enhanced. Thus, a user may be associated with ‘multiple identities’ using a single credential, namely the private key.

In an embodiment, the public keys may be used as identifiers in the first database such that the identifiers are database identifiers. In this case, the method preferably comprises depositing data into the database using the identifiers. For example, the data may comprise medical datasets of a patient, the patient being the owner of the private key, wherein the medical datasets may be stored in the database sorted by medical topics. In this case, an individual public key of the set of public keys of the patient may be associated with a certain medical topic. Thus, the medical datasets are not stored in the database using one common identifier for all medical topics, but the datasets are stored in a distributed manner in the database using a set of identifiers with a different identifier for each medical topic. Nevertheless, by means of his one private key the patient is able to individually generate the set of public keys for access to the datasets stored in the database.

It has to be noted that various computer implemented schemes for providing an identifier for a database exist with the identifier being for instance a pseudonym. A pseudonym is typically used for protecting the informational privacy of a user. Such computer implemented schemes for providing a pseudonym typically enable the disclosure of identities of anonymous users if an authority requests it, if certain conditions are fulfilled. For example, Benjumea et al, Internet Research, Volume 16, No. 2, 2006 pages 120-139 devise a cryptographic protocol for anonymously accessing services offered on the web whereby such anonymous accesses can be disclosed or traced under certain conditions.

However, even in case absolute anonymity is guaranteed using a certain pseudonym, with an increasing amount of data the risk increases that by means of data correlation techniques applied on the data stored with respect to said pseudonym, conclusions can be drawn from said data about the owner of the pseudonym. Further, a large number of different features stored with respect to a person increases the probability that the person's identity can be revealed, for example by means of the combination of the ZIP code, age, profession, marital status and height. Thus, with an increasing amount of data stored with respect to a pseudonym, the risk of breaking the user's anonymity is also increasing.

By means of the above mentioned method of using a private key from which a whole set of public keys is calculated, correlation attacks are more likely to fail since correlations can only be detected for a given single identifier.

The term ‘database’ as used herein is a collection of logically-related data or files containing data that provide data for at least one use or function. Databases are essentially organized data that may be provided or used by an application. Examples of a database include, but are not limited to: a relational database, a file containing data, a folder containing individual data files, and a collection of computer files containing data.

In accordance with an embodiment of the invention, the identifier corresponds to a public key of the first user.

In accordance with an embodiment of the invention, the identifier is a pseudonym of the first user and/or the identifier is an access key to the data in the database.

In accordance with an embodiment of the invention, analyzing the retrieved data is performed by an inference engine. Herein, the term ‘inference engine’ is understood as any device or computer program that derives answers from the database. Inference engines are considered to be a special case of reasoning engines, which can use more general methods of reasoning. In an embodiment, analyzing the data can be performed by a decision support system, e.g. in the medical field for evaluating a user's individual medical data and processing the data by rules. The result of the evaluation and processing by rules may be hints and recommendations to the physician regarding the user's health condition and further treatment.

In accordance with an embodiment of the invention, the method further comprises retrieving a digital signature of the data stored in the first database along with the data and verifying the digital signature using the public key of the first user. Thus, the public key of the first user has two purposes. First, it is used as an identifier for the user's data in the database. Second, it is used in order to verify for example the integrity of the user's data by applying the user's public key to the digital signature of the data. This significantly simplifies the data analysis process since no further actions have to be taken in order to ensure the data integrity. Only the first user is able to sign his data using his private key—which is only known to the first user. Consequently, counterfeiting of the user's data is not possible and also errors which occurred during data storage in the database can easily be detected.

In accordance with an embodiment of the invention, providing the result of the analysis comprises sending the result to said first user with the recipient address to which the result is sent comprising the public key.

This has the advantage, that a ‘blind messaging’ can be performed. Thus, the recipient's identity is not revealed when sending the result to the first user with the recipient address to which the result is sent comprising the first user's public key. Further, even though the data is stored in the first database associated with the public key of the first user, it will not be possible to identify the respective ‘real person’ that is associated with said public key of the first user even when having full access to said database.

Since with the continuously increasing amount of personal data stored in databases with respect to individual persons, the people consciousness regarding data privacy protection increases. This results in the problem that on the one hand personal data has to remain available for data analysis systems like the above mentioned clear text processing sites, wherein the data analysis system must be able to provide an analysis result to the owner of the data. On the other hand, data privacy protection has to be ensured. By providing the result of the analysis to the first user by sending the result to said first user with the recipient address to which the result is sent comprising the public key, this conflict is solved in an elegant but safe manner.

It has to be noted here, that generally the ‘result of the analysis’ is understood as either the direct outcome of the analysis performed on the first user's data, or as an indirect outcome of the analysis performed on the first user's data. In a practical embodiment, in case the analysis is performed with respect to a determination if based on the user's data the user qualifies for participation in a certain disease management program (DMP), the result of the analysis may either be ‘qualified for DMP xyz’ which is considered as a direct outcome of the analysis, or the result of the analysis may just be ‘please consult a medical doctor’.

Similarly, in case the data is medical data, the result of the analysis may comprise a laboratory value like ‘liver function test results a value of 1234’ or it may comprise an advice ‘stop drinking alcohol’. However, the invention is not limited to medical data but may comprise any kind of user data like personal qualifications, personal documents, information about a user's daily requirements regarding purchased convenience goods, information about water and electricity consumption etc.

In accordance with an embodiment of the invention, the recipient address corresponds to the public key of the first user. However, the invention is not limited to this specification. For example, it may be possible to add a domain name to the public key of the first user such to make such kind of messaging compatible to already existing internet messaging systems: the invention thus either permits to direct a result directly to the address ‘public_recipient_key’ or to direct the result to for example the email address ‘public_recipient_key@securedomain.com’.

In case of SMS messaging in mobile telecommunication networks, for example the message comprising the result may be directed to a central provider telephone number, wherein the body of the SMS message may contain the public key of the first user and the message ‘message’ like for example ‘public_recipient_key message’.

The skilled person will understand that there are further possibilities to realize the basic idea according to the invention in various messaging environments.

In accordance with an embodiment of the invention, said result is sent encrypted with the public key to the first user. Thus, again the public key of the first user has a double purpose: the first purpose is the usage as anonymous recipient address and the second purpose is the usage as encryption key. Since only the recipient possesses the private key, only he will be able to decrypt the message. Thus, in a highly convenient manner, secure messaging can be performed in an anonymous manner, wherein only one type of information is required to be known by the sender: the public key.

In accordance with an embodiment of the invention, said result is sent from a second user, wherein a sender asymmetric cryptographic key pair is associated with the second user, said key pair comprising a public sender key and a private sender key, the method further comprising generating a signature of the result using the private sender key and sending the signature to said first user. This further enables the first user to verify the authenticity of the result in a very convenient manner. Preferably, the public sender key is available in a respective database such that it is possible to also verify that the sender of the message is an ordinary member of the group of participants which is allowed to send results to the recipient. For example, the second user may be the provider of the data processing component.

Referring back to the above mentioned example of providing advises to the first user based on the outcome of the analysis of his data, the use of digital signatures ensures that the first user is protected from fake information or fake advises of third parties which would confuse or even misguide the first user.

In accordance with an embodiment of the invention, the message is a synchronous or asynchronous conferencing message. For example, synchronous conferencing may comprise any kind of data conferencing, instant messaging, Internet Relay Chat (IRC), videoconferencing, voice chat, or VoIP (voice over IP). Asynchronous conferencing may comprise email, Usenet, SMS or MMS.

In accordance with an embodiment of the invention, the message is an email message with the message being sent to the first user by email, wherein the email address comprises the public key of the first user. For example, in this case the public key of the first user is comprised in the header of the email as the recipient address to which the message is sent, wherein the message is comprised in the body of the email. Variations like having the public key of the first user being comprised in the body with the message being sent to a central email service with central email address are also possible.

In another aspect, the invention relates to a computer implemented method for receiving a result from a second user of a data processing component of a network cloud by a first user, wherein an asymmetric cryptographic key pair is associated with the first user, said key pair comprising a public key and a private key, the method comprising receiving the result by said first user with the recipient address at which the result is received comprising the public key.

In another aspect, the invention relates to a computer implemented method for storing data of a first user or a second user in a database of a network cloud, the first user having a private key, the method comprising calculating a set of public keys, wherein the private key and each public key of the set of public keys form an asymmetric cryptographic key pair, storing the data encrypted with one of the public keys and assigned to the first user in the second database or storing the data pseudonymously in the first database with the data being assigned to an identifier, wherein the identifier comprises one of the public keys.

In accordance with a further embodiment of the invention, the method further comprises generating a digital signature for the data using the private key, wherein the digital signature is stored into the database along with the data. This embodiment is particularly advantageous because the digital signature for the data allows authentication of the data. In this way the authorship of the data can be verified.

In accordance with a further embodiment of the invention, the method further comprises directly receiving the private key or generating the private key, wherein generating the private key comprises receiving an input value and applying a cryptographic one-way function to the input value for generation of the private key, wherein the cryptographic one-way function is an injective function.

In accordance with an embodiment of the invention, the method further comprises the step of depositing data into the first database using the identifier. This embodiment is advantageous because the identifier may be used to control access to the database. Alternatively the identifier could be used as a pseudonym for which data deposited into the database is referenced against. This provides anonymity for a user. Thus, some embodiments of the present invention are particularly advantageous as an extremely high degree of protection of the informational privacy of users is provided. This is because an assignment of the user's identity to the user's pseudonym does not need to be stored and that no third party is required for establishing a binding between the pseudonym and the user's identity. Some embodiments of the present invention enable to generate a user's pseudonym in response to the user's entry of a user-selected secret whereby the pseudonym is derived from the user-selected secret. As the user-selected secret is known only by the user and not stored on any computer system there is no feasible way that a third party could break the informational privacy of the user, even if the computer system would be confiscated such as by a government authority.

This enables to store sensitive user data, such as medical data, in an unencrypted form in a publicly accessible database. The user's pseudonym can be used as a database identifier, e.g. a primary key or candidate key value that uniquely identifies tuples in a database relation, for read and write access to data objects stored in the database.

In accordance with a further embodiment of the invention, the public key of the first user or the set of public keys is calculated from the private key using elliptic curve cryptography, wherein said calculation is performed by a variation of the domain parameters used for performing the elliptic curve cryptography. For the case of simplicity, only one parameter of the domain parameters is varied here accordingly. For example, in a first step of calculating a first public key the private key and a first base point and a set of further domain parameters may be used. The first public key is calculated using asymmetric cryptography which is implemented using elliptical curve cryptography. Then, the first base point is replaced by a second base point that is not inferable from the first base point in an easy way in the domain parameters, wherein the other domain parameters are kept unmodified. Finally, a second public key is calculated by elliptic curve cryptography using the private key, the second base point and the set of unmodified further domain parameters.

However, the invention is not limited to a variation of base points for calculating the set of public keys—any of the domain parameters may be varied for this purpose. Nevertheless, a base point variation is preferred since this provides a computationally efficient way to compute multiple identifiers for a given user in a secure way. Furthermore, it is by far more complicated to vary one or more of the other domain parameters because doing this would result in a different elliptic curve that would have to fulfill many conditions in order to be considered valid.

This embodiment is advantageous because a single private key has been used to generate a set of public keys to be used as identifiers. This is particularly advantageous because the public keys cannot be inferred from each other supposed their respective base points cannot be either, yet only a single input value is needed for all of them. In other words, in case of a base point variation, knowledge of one of the public keys does not allow an attacker to determine any other public key. The used public keys are therefore not correlatable. However, all of the public keys are determined by a single input value or private key. It has to be noted that preferably the base points are meant to be public. Nevertheless, an embodiment of the invention where the base points are at the user's discretion may also be possible.

In accordance with a further embodiment of the invention, the method further comprises either directly receiving the private key or generating the private key, wherein generating the private key comprises receiving an input value and applying a cryptographic one-way function to the input value for generation of the private key, wherein the cryptographic one-way function is an injective function.

This embodiment has the advantage that a user may either directly use a private key for the generation of the identifiers, or alternatively he may use a certain input value from which the private key may be calculated. The input value may be a user-selected secret.

The term ‘user-selected secret’ is understood herein as any secret data that is selected by or related to a user, such as a user-selected secret password or a secret key, such as a symmetric cryptographic key. Further, the term ‘user-selected secret’ does also encompass a combination of biometric data obtained from the user and a user-selected password or secret key, such as a biometric hash value of the password or secret key.

In accordance with a further embodiment of the invention, the method further comprises receiving the user-selected secret as the input value, storing the user-selected secret in a memory, computing the private key by applying an embedding and/or randomizing function onto the secret, storing the private key in the memory, computing the set of public keys using the private key and erasing the secret and the private key from the memory.

The term ‘memory’ as used herein encompasses any volatile or non-volatile electronic memory component or a plurality of electronic memory components, such as a random access memory. Examples of computer memory include, but are not limited to: RAM memory, registers, and register files of a processor.

The term ‘embedding function’ or ‘embedding component’ as used herein encompasses any injective function that maps the elements of an n-dimensional space onto elements of an m-dimensional space, where n>m. For the purpose of this invention, we focus on embedding functions where m=1. In accordance with embodiments of this invention n is equal to 2 and m is equal to 1 for combining two elements onto a single element. In one embodiment, a user-selected secret and a public parameter are mapped by the embedding function to the 1-dimensional space to provide a combination of the user selected secret and the public parameter, e.g. a single number that embeds the user selected secret and the public parameter. This single number constitutes the embedded secret. In another embodiment, a first hash value of the user selected secret and a random number are mapped by the embedding function to the 1-dimensional space to provide the embedded secret.

A ‘randomizing function’ or ‘randomizing component’ as understood herein encompasses any injective function that provides an output of data values that are located within a predefined interval and wherein the distribution of the data values within the predefined interval is a substantially uniform distribution.

The term ‘embedding and randomizing function’ as used herein encompasses any function that implements both an embedding function and a randomizing function.

Even though any known method for generation of asymmetric cryptographic keys may be employed in order to carry out the invention, the embodiment employing the user-selected secret for generating the public key and the private key(s) is particularly advantageous as an extremely high degree of protection of the informational privacy of users is provided. This enables to store sensitive user data, such as medical data, even in an unencrypted form in a publicly accessible database. A user's public key can be used as the database identifier, e.g. a primary key or candidate key value that uniquely identifies tuples in a database relation, for access to data objects stored in the database.

The usage of an embedding and/or randomizing function is advantageous because the input value may be clear text or an easily guessed value. By using an embedding and/or randomizing function a pseudonym which is more difficult to decrypt may be constructed.

In accordance with an embodiment of the invention, at least one public parameter is used for applying the embedding and randomization function. A public parameter may be the name of the user, an email address of the user or another identifier of the user that is publicly known or accessible. A combination of the user-selected secret and the public parameter is generated by the embedding component of the embedding and randomization function that is applied on the user-selected secret and the public parameter.

The combination can be generated such as by concatenating the user-selected secret and the public parameter or by performing a bitwise XOR operation on the user-selected secret and the public parameter. This is particularly advantageous as two users may by chance select the same secret and still obtain different identifiers as the combinations of the user-selected secrets with the user-specific public parameters differ.

In accordance with an embodiment of the invention, the embedding component of the embedding and randomizing function comprises a binary cantor pairing function. The user-selected secret and the public parameter are embedded by applying the binary cantor pairing function on them.

In accordance with an embodiment of the invention, the randomizing component of the embedding and randomizing function uses a symmetric cryptographic algorithm like the Advanced Encryption Standard (AES) or the Data Encryption Standard (DES) by means of a symmetric key. This can be performed by encrypting the output of the embedding component of the embedding and randomizing function, e.g. the binary cantor pairing function, using AES or DES.

In accordance with an embodiment of the invention, the symmetric key that is used for randomization by means of a symmetric cryptographic algorithm is user-specific. If the symmetric key is user-specific, the use of a public parameter can be skipped, as well as embedding the user-selected secret and the public parameter; the randomizing function can be applied then solely on the user-selected secret. By applying a symmetric cryptographic algorithm onto the user-selected secret using a user-specific symmetric key embedding can be skipped and randomization of the user-selected secret is accomplished. If the symmetric key is not user-specific, the use of the public parameter and embedding the user-selected secret and the public parameter are necessary.

In accordance with an embodiment of the invention, the embedding and randomizing function is implemented by performing the steps of applying a first one-way function on the user-selected secret to provide a first value, providing a random number, embedding the random number and the first value to provide a combination, and applying a second one-way function on the combination to provide a second value, wherein the second value constitutes the private key. This embodiment is particularly advantageous as it provides a computationally efficient method of implementing an embedding and randomization function.

In accordance with an embodiment of the invention, it is determined whether the output of the embedding and randomizing function fulfils a given criterion. For example, it is checked whether the output of the embedding and randomization function is within the interval between 2 and n−1, where n is the order of the elliptic curve. If the output of the embedding and randomizing function does not fulfill the criterion another random number is generated and the embedding and randomization function is applied again to provide another output which is again checked against the criterion. This process is performed repeatedly until the embedding and randomizing function provides an output that fulfils the criterion. The output is then regarded as the private key that is used to calculate the public key, by multiplying the private key with the first base point.

In another aspect, the invention relates to a computer program product comprising computer executable instructions to perform any of the method steps described above.

In another aspect, the invention relates to a cloud network for performing cloud computing on data of a first user, the cloud comprising cloud components, the cloud components comprising a first database and a data processing component, wherein an asymmetric cryptographic key pair is associated with the first user, said asymmetric cryptographic key pair comprising a public key and a private key, the data being stored pseudonymously and non-encrypted in the first database with the data being assigned to an identifier, wherein the identifier comprises the public key, wherein the data processing component is adapted for retrieving the data from the first database, wherein retrieving the data from the first database comprises receiving the identifier and retrieving the data assigned to the identifier from the first database, wherein the data processing component is further adapted for processing the retrieved data and providing a result of the analysis.

In another aspect, the invention relates to a computer system for receiving a result from a second user of a network cloud by a first user, wherein an asymmetric cryptographic key pair is associated with the first user, said key pair comprising a public key and a private key, the system comprising means for receiving the result by said first user with the recipient address at which the result is received comprising the public key.

The term ‘computer system’ as used herein encompasses any device comprising a processor. The term ‘processor’ as used herein encompasses any electronic component which is able to execute a program or machine executable instructions. References to the computing device comprising “a processor” or a “microcontroller” should be interpreted as possibly containing more than one processor. The term ‘computer system’ should also be interpreted to possibly refer to a collection or network of computing devices each comprising a processor. Many programs have their instructions performed by multiple processors that may be within the same computing device or which may be even distributed across multiple computing devices.

In accordance with an embodiment of the invention, the system either comprises means for directly receiving the private key or means for receiving an input value, wherein the processor means are further operable for generating the private key, wherein generating the private key comprises applying a cryptographic one-way function to the input value for generation of the private key, wherein the cryptographic one-way function is an injective function.

In accordance with an embodiment of the invention, the input value is a user-selected secret, the system further comprising a memory for storing the user-selected secret and a private key and a processor operable for executing instructions stored in the memory, wherein the memory contains instructions for performing the steps of:

-   -   storing the user-selected secret in the memory;     -   computing the private key by applying an embedding and/or         randomizing function onto the secret;     -   storing the private key in the memory;     -   computing the set of public keys using the private key; and     -   erasing the secret and the private key from the memory.

In another aspect, the invention relates to a computer system for storing data of a first user in a first or a second database of a network cloud, the first user having a private key, the system comprising:

-   -   processor means for calculating a set of public keys, wherein         the private key and each public key of the set of public keys         form an asymmetric cryptographic key pair,     -   means for storing the data encrypted with one of the public keys         and assigned to the first user in the second database or     -   means for storing the data pseudonymously in the first database         with the data being assigned to an identifier, wherein the         identifier comprises one of the public keys.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following embodiments of the invention are explained in greater detail, by way of example only, making reference to the drawings in which:

FIG. 1 is a block diagram of a first embodiment of a computer system of the invention,

FIG. 2 is a flowchart being illustrative of an embodiment of a method of the invention,

FIG. 3 is a block diagram of a further embodiment of a computer system of the invention,

FIG. 4 is a flowchart being illustrative of a further embodiment of a method of the invention,

FIG. 5 is a flowchart being illustrative of a further embodiment of a method of the invention,

FIG. 6 is a flowchart being illustrative of a further embodiment of a method of the invention.

DETAILED DESCRIPTION

Throughout the following detailed description like elements of the various embodiments are designated by identical reference numerals.

FIG. 1 shows a cloud network for performing cloud computing on data objects. The cloud network comprises cloud components which comprise a first pseudonymous database 138, a second database 156 and an analytic system 144. Further, the cloud components comprise a computer system 100 of a user.

Without loss of generality, in the following the scenario is assumed that user data comprises medical data, wherein the analytic system 144 is part of a computer system of a medical doctor. As a starting point, medical data objects 120 may have to be stored in the database 156 in an encrypted manner.

For this purpose, the computer system 100 that has a user interface 102 for a user's entry of a user-selected secret 112 that is designated as s_(T) in the following. For example, a keyboard 104 may be coupled to the computer system 100 for entry of s_(T). Instead of a keyboard 104 a touch panel or another input device can be coupled to the computer system 100 for entry of s_(T). In addition, a sensor 106 can be coupled to the computer system 100 such as for capturing biometric data from a biometric feature of the user. For example, the sensor 106 may be implemented as a fingerprint sensor in order to provide biometric fingerprint data to the computer system 100.

A public parameter, such as the user's name or email address, can also be entered into the computer system 100 via the keyboard 104 or otherwise. For example, a personal set V_(T,i) containing at least one user-specific public parameter, such as the user's name or email address, is entered into the computer system 100 by the user T_(i).

The computer system 100 has a memory 108, such as a random access memory, and at least one processor 110. The memory 108 serves for temporary storage of the user-selected secret s_(T) 112, a combination 114 of s_(T) 112 and V_(T,i), a private key 116, a public key 118 that constitutes an identifier for a database and/or pseudonym of the user T_(i), and a data object 120, such as a medical data object containing medical data related to the user T_(i). Further, the memory 108 serves for computer program instructions 122 to be loaded for execution by the processor 110.

The computer program instructions 122 provide an embedding and randomizing function 126, a key generator 128 and may also provide a database access function 130 when executed by the processor 110. Further, the instructions 122 may provide data encryption and decryption capabilities to the computer 100.

The embedding and randomizing function 126 may be provided as a single program module or it may be implemented by a separate embedding function 132 and a separate randomizing function 134. For example, the embedding function 132 or an embedding component of the embedding and randomization function 126 provides the combination 114 by concatenating s_(T) and the user's name or by performing a bitwise XOR operation on s_(T) and the user's name.

In one implementation, the embedding and randomizing function 126 implements symmetric encryption provided by a symmetric cryptographic algorithm, e.g. AES, using a user-specific symmetric key for encryption of the user-selected secret 112. This provides randomizing of s_(T) 112, while embedding can be skipped.

In another implementation, the embedding function 132 is implemented by a binary cantor pairing function for embedding s_(T) 112 and V_(T,i), and the randomizing function 134 is implemented by AES encryption using a symmetric key that is the same for the entire set of users T.

In still another embodiment the embedding and randomizing function 126 is implemented by an embedding function, two different hash functions and a random number generator (cf. the embodiment of FIGS. 3 and 4).

The purpose of the embedding and randomizing function 126 is to calculate the private key 116, as will be described in detail with respect to FIG. 4.

The key generator 128 serves to compute public key 118 using elliptic curve cryptography (ECC). The base point given by the domain parameters of the elliptic curve is multiplied by the private key 116 which provides the public key 118. By varying the base point and leaving the other domain parameters of the elliptic curve unchanged multiple identifiers and/or pseudonyms comprising respective public keys can be computed for the user T_(i) on the basis of the same secret s_(T). Thus, this results in a set of public keys.

The computer system 100 may have a network interface 136 for coupling the computer system 100 to the database 156 via a communication network 140, such as the Internet. The database access function 130 enables to perform a write and a read access for accessing the data object 120 stored in the database 156 encrypted with the public key 118, wherein the encrypted data object is denoted by reference numeral 158.

The analytic system 144 comprises a component 146 for analyzing data objects of the users T, such as by data mining or data clustering. In one application the data objects contain medical data of the various users. By analyzing the various data objects using techniques such as data mining and/or data clustering techniques, medical knowledge can be obtained. For example, data clustering may reveal that certain user attributes contained in the medical data increase the risk for certain diseases.

As mentioned above, it is assumed that the analytic system 144 is part of a computer system of a medical doctor. In detail, the analytic system 144 is a clear text processing site which can only analyze clear text, i.e. non encrypted data.

In case the encrypted data 158 comprises medical records of a certain user, on a visit with a medical doctor the user may wish to provide these medical records to the doctor in order to enable him a detailed review on a course of disease of said user. For this reason, the user may use his computer system 100 and read the encrypted data 158 from the database 156 using the database access function 130. Then, using the program 122 he may decrypt the encrypted data 158 which results in the data object 120. Data decryption is performed employing the user's private key 116 which may be generated on demand by the computer 100 when receiving the user selected secret 112 and the public parameter, as described above.

In a subsequent step, the ‘clear text’ data, i.e. the data object 120 will be stored in the database 138. The network interface 136 also serves for coupling the computer system 100 to the database 138 via the communication network 140, wherein the database access function 130 further enables to perform a write and a read access for accessing the data object 120 to be stored in the database 138 using the public key 118 as a database access key, e.g. a primary key, candidate or foreign key value that uniquely identifies tuples in a database relation. Alternatively, the public key 118 may be used as a pseudonym, wherein the data object 120 is to be stored associated with the pseudonym in the database 138.

As mentioned above, it is preferred not to store multiple data objects 120 in the database 138 using only one identifier, since data correlation analysis performed on said data objects 120 may yield information which may enable to identify the user, i.e. owner of said data objects. Instead, the data objects are stored in the database 138 in a distributed manner with different data objects 120 being accessible with different public keys 118, wherein the private key 116 and each public key of the set of public keys form an asymmetric cryptographic key pair.

After having stored the data object 120 in the database 138 using the public key 118 as the database access key, the user may provide the public key 118 to the analytic system 144. In turn, using the public key 118, the system 144 is able to access the database 138, retrieve the data object 120 stored with respect to said public key 118 and perform an analysis on the data object 120 using its component 146 for analyzing the data objects.

In an embodiment, the analytic system 144 may be a decision support system (DSS) or generally an inference engine. In one application, the data objects stored in the database 138 contain medical data of the various users. By analyzing the various data objects using techniques such as data mining and/or data clustering techniques, medical knowledge can be obtained. For example, data clustering may reveal that certain user attributes contained in the medical data increase the risk for certain diseases.

It has to be noted here, that generally the computer system 100 may be part of a computer system at a medical doctor. When having a visit with the doctor, the patient, i.e. the user, may enter his or her required parameters like the secret 112 in order to permit the computer system to perform the steps of data retrieval and pseudonymous data storage as described above. After these steps are completed, the doctor may send a command to the analytic system 144 for starting an analysis on the patient's data. The analytic system may also be part of the computing system 100, or it may be an external system implemented in hardware or software in the network cloud.

The outcome of the analysis performed by the system 144 may be provided by the analytic system 144 to the users T, i.e. the owners of the records stored in the database 138. Sending the result of the individual analysis of the records of each user to the respective users may be performed by any kind of messaging, as described above. Preferably, the recipient address to which a respective analysis result is sent comprises the public key of the respective user. Reception of the result may be performed using the system 100 via its interface 136 and a dedicated reception component implemented by hardware or software.

In an alternatively preferred embodiment, the outcome of the analysis is stored again in the database 138, associated with the user public key 118 as the database access key. Thereupon, the outcome of the analysis may be read by the computer system 100, encrypted using the public key 118 and stored in the database 156. Finally, the data objects and analysis results stored with respect to the public key 118 in the database 138 may be deleted from said database 138, since they are not required any more.

It will be understood that the above described steps constitute only one possible embodiment of the invention. Variations are possible. For example, in case a multitude of public keys is generated from a single private key, the public keys used for temporal data storage in the database 138 may be keys of the medical doctor owning the system 100. Thus, the system 100 may serve two purposes, namely data encryption and decryption using the patient's (user's) asymmetric cryptographic key pairs, as well as temporal data storage in the database 138 and initiation of the data mining process via the analytic system 144 using the medical doctor's asymmetric cryptographic key pairs. Of course, this requires that the patient (user) entrusts the medical doctor with his medical data—which nevertheless is usually the case.

Referring back to the generation of the private key 116 and the public key(s) 118, for generating a pseudonym p_(T,i), for a user T_(i) based on the secret s_(T) 112 and domain parameters D_(i) containing a base point for the elliptic curve cryptography the following steps are executed by the computer system 100 in operation:

The user T_(i) enters his or her user-selected secret s_(T) 112 such as via the keyboard 104. In addition, the user may enter at least one public parameter V_(T,i) such as his name or email address via the keyboard 104 or otherwise. Such a public parameter V_(T,i) may also be permanently stored in the computer system 100.

The secret s_(T) 112 is temporarily stored in the memory 108. Upon entry of the secret s_(T) 112 the embedding function 132 or the embedding component of the embedding and randomizing function 126 generates the combination 114 of the secret s_(T) 112 and the public parameter V_(T,i). The resultant combination 114 is temporarily stored in the memory 108.

Next, the randomizing function 134 or the randomizing component of the embedding and randomizing function 126 is invoked in order to calculate the private key 116 on the basis of the combination 114. The resultant private key 116 is temporarily stored in memory 108. In the next step, the key generator 128 is started for computing the public key 118 by multiplying the base point contained in the domain parameters D_(i) of the elliptic curve being used by the private key 116.

The public key 118, which is the identifier, i.e. in one embodiment the pseudonym p_(T,i), is stored in memory 108. The secret s_(T) 112, the combination 114 as well as the private key 116 as well as any intermediate result obtained by execution of the embedding and randomizing function 126 and the key generator 128 are then erased from the memory 108 and/or the processor 110. As a consequence, there is no technical means to reconstruct the assignment of the resultant pseudonym to the user T_(i) as only the user knows the secret s_(T) 112 that has led to the generation of his or her pseudonym p_(T,i). A data object 120 containing sensitive data of the user T_(i), such as medical data, can then be stored by execution of the database access function 130 in the pseudonymous database 138 using the pseudonym p_(T,i) 118 as a database access key, e.g. a primary key or candidate key value that uniquely identifies tuples in a database relation.

The user-selected secret s_(T) 112 may be obtained by combining a user-selected password or secret key with biometric data of the user T_(i) that is captured by the sensor 106. For example, a hash value of the user-selected password or secret key is calculated by execution of respective program instructions by the processor 110. In this instance the hash value provides the user-selected secret s_(T) 112 on which the following calculations are based.

A plurality of users from the public set of enrolled participants T may use the computer system 100 to generate respective pseudonyms p_(T,i) and to store data objects containing sensitive data, such as medical information, in the database 138 as it has been described above in detail for one of the users T_(i) by way of example.

For reading the data object of one of the users T_(i) from the database 138, the user has to enter the secret s_(T) 112. Alternatively, the user has to enter the user-selected password or secret key via the keyboard 104 and an acquisition of the biometric data is performed using the sensor for computation of a hash value that constitutes s_(T) 112. As a further alternative, the secret key is read by the computer system from an integrated circuit chip card of the user. On the basis of s_(T) 112 the pseudonym can be computed by the computer system 100.

The above mentioned steps may be repeated several times for the generation of the set of identifiers from a single secret s_(T) 112 or a single private key 116, wherein preferably only the base point is varied.

FIG. 2 shows a corresponding flowchart.

In step 200 the user T_(i) enters his or her user-selected secret s_(T) and public parameter V_(T,i). In step 202 s_(T) and V_(T,i) are combined to provide the first combination 114 by the embedding function (cf. embedding function 132 of FIG. 1). Next, the randomizing function (cf. randomizing function 134 of FIG. 1) is applied on s_(T) and V_(T,i) in step 204 which provides a private key. As an alternative, an embedding and randomizing function 126 is applied on s_(T) and V_(T,i) which provides the private key.

In step 206 a public key is computed using the private key obtained in step 204 and the public key is used in step 208 as a pseudonym of the user T_(i). For example the pseudonym may be used as a database identifier, e.g. a primary key or candidate key value that uniquely identifies tuples in a database relation for storing a data object for the user T_(i) in a database with pseudonymous data (cf. database 138 of FIG. 1).

When carrying out step 206, the public key is calculated from the private key using elliptic curve cryptography, wherein said calculation is performed by a variation of the domain parameters used for performing the elliptic curve cryptography. For example, a base point variation may be performed for this purpose.

Even though, the above description always speaks about using the public key as pseudonym and using the pseudonym as a database access key, the invention is not limited to this embodiment. For example, the public keys generated using the steps above may only be a part of respective database access keys or pseudonyms, i.e. they may be comprised in the access keys or the pseudonyms. An example may be that the public key is given by ‘FF06763D11A64’, wherein the identifier used for accessing data in a database named ‘xyz’ may be given by ‘xyz—FF06763D11A64’.

FIG. 3 shows a further embodiment of computer system 100. In the embodiment considered here the embedding and randomizing function 126 comprises an embedding function 132, a random number generator 148, a first hash function 150 and a second hash function 152. In the embodiment considered here the computation of the private key 116 based on s_(T) 112 may be performed as follows:

The first hash function 150 is applied on the user-selected secret s_(T) 112. This provides a first hash value. Next, a random number is provided by the random number generator 148. The random number and the first hash value are combined by the embedding function 132 to provide the combination 114, i.e. the embedded secret s_(T) 112.

The combination of the first hash value and the random number can be obtained by concatenating the first hash value and the random number or by performing a bitwise XOR operation on the first hash value and the random number by the embedding function 132. The result is a combination on which the second hash function 152 is applied to provide a second hash value. The second hash value is the private key 116 on which the calculation of the public key 118 is based.

Dependent on the implementation it may be necessary to determine whether the second hash value fulfils one or more predefined conditions. Only if such conditions are fulfilled by the second hash value it is possible to use the second hash value as the private key 116 for the following computations. If the second hash value does not fulfill one or more of the predefined conditions, a new random number is provided by the random number generator 14,8 on the basis of which a new second hash value is computed, which is again checked against the one or more predefined conditions (cf. the embodiment of FIG. 4).

The random number on the basis of which the private key 116 and thereafter the public key 118 has been computed is stored in a database 154 that is coupled to the computer system 100 via the network 140. The random number may be stored in the database 154 using the public parameter V_(T,i) as the database identifier for retrieving the random number for reconstructing the pseudonym at a later point of time.

By means of the system 100, a set of identifiers comprising different public keys 118 is generated using the single secret 112 or directly the single private key 116, wherein for example in case of elliptic curve cryptography only the base point of a set of domain parameters is varied for this purpose. Individual base points 190 used for generation of the individual public keys 118 may also be stored in the memory 108 of the computing system 100. Alternatively, the base points may be stored in the database 154 or any other database external to the system 100.

Generated identifiers may be used for accessing the database 138 using the module 130, which was described with respect to FIG. 1.

The user T_(i) may use the public key provided by the computer system 100 for sending a message comprising data to an address comprising the public key or to an address which consists of the public key. For example, the user may send a message to the database 138. The message may comprise the decrypted data object 120 of the user, wherein upon reception of the message by the database 138, the database 138 may store the data object assigned to the user's public key in a pseudonymous manner.

It has to be noted that knowledge of the user's public key permits the user T_(i) to send information to his messaging account, as well as any other institution or device or person who knows the user's public key 118 to send information to the user T_(i). As discussed with respect to FIG. 1, the analytic system 144 may analyze content of the database 138, wherein data of a certain user T_(i) is stored data assigned to an identifier, wherein the identifier comprises the public key of this user. Analysis of the content of the database 138 may result in the public key of the certain user T_(i), as well in an analysis result. Thereupon, the analytic system 144 may send this result as a message or in a message using a recipient address comprising the determined public key of the certain user T_(i). The message will then be received either directly by the user via the computing system 100, or via a message provider.

In the general case when a user T₁ wants to send a message to user T₂, this requires that user T₁ is able to obtain the messaging address of T₂. For this purpose, he may access a PKI (public key infrastructure) from which the address may be obtained.

According to an embodiment, access to the PKI may be performed by the user T₁ by using a pseudonym of the user T₂. It has to be noted that this pseudonym is not to be confused with the pseudonym comprising the public user key. Here, the pseudonym may be any identifier which is associated in a database of the PKI with the user's messaging address. Thus, the user T₂ may provide his pseudonym to user T₁ which may then access the PKI for retrieval of the respective messaging address of user T₂.

Generally, for reconstructing the public key the user has to enter his or her user-selected secret s_(T) 112 into the computer system on the basis of which the first hash value is generated by the hash function 150, and the combination 114 is generated by the embedding function 132 or the embedding component of the embedding and randomizing function 126 using the first hash value and the random number retrieved from the database 154.

Depending on the implementation, the user may also need to enter the user's public parameter V_(T,i). A database access is performed using the user's public parameter V_(T,i) as a database identifier, e.g. a primary key or candidate key value that uniquely identifies tuples in a database relation, in order to retrieve the random number stored in the database 154.

In other words, the reconstruction of the private key 116 is performed by applying the embedding function 132 on the first hash value obtained from the user-selected secret s_(T) 112 and the retrieved random number which yields the combination 114. The first hash value is combined with the random number retrieved from the database 154 by the embedding function 132 to provide the combination onto which the second hash function 152 is applied which returns the private key 116, out of which the public key 118, i.e. the identifier, can be computed. After the user T_(i) has recovered his or her identifier a database access for reading and/or writing from or to the database 138 may be performed or the user may log into an online banking system for performing online banking transactions using his identifier as a TAN.

FIG. 4 shows a respective flowchart for generating a pseudonym p_(T,i) for user T_(i). In step 300 the user enters the user-selected secret s_(T). In step 304 a first hash function is applied on the user-selected secret s_(T) which provides a first hash value. In step 306 a random number is generated and in step 308 an embedding function is applied on the first hash value and the random number to provide a combination 114 of the first hash value and the random number. In other words, the first hash value and the random number are mapped to a 1-dimensional space, e.g. a single number, by the embedding function. The combination 114 can be obtained by concatenating the random number and the first hash value or by performing a bitwise XOR operation on the first hash value and the random number.

In step 310 a second hash function is applied on the combination which provides a second hash value. The second hash value is a candidate for the private key. Depending on the implementation the second hash value may only be usable as a private key if it fulfils one or more predefined conditions. For example, if ECC is used, it is checked whether the second hash value is within the interval between 2 and n−1, where n is the order of the elliptic curve.

Fulfillment of such predefined conditions is checked in step 312. If the condition is not fulfilled, the algorithm returns to step 306. If the condition is fulfilled, then the second hash value qualifies to be used as a private key in step 314 to compute a respective public key providing an asymmetric cryptographic key-pair consisting of the private key and the public key. In step 316 the public key computed in step 314 is used as an identifier such as for accessing a pseudonymous database or other purposes.

In case elliptic curve cryptography is used in step 314 for generating the public key, in step 318 a single domain parameter is varied, preferable a base point, wherein all other base points are left unmodified. However, also more than one domain parameter may be modified in step 318. Afterwards, using the modified domain parameter(s), steps 314 and 316 are repeated which results in a further public key which can be used as an identifier.

The method with steps 318, 314 and 316 may be repeated as often as necessary in order to generate a desired set of identifiers.

FIG. 5 shows a block diagram which illustrates an embodiment of the method according to the invention. In step 500 an input value is accessed. The input value may be stored in a computer memory or computer storage device or the input value may be generated. For example, the input value could be generated from a user-selected secret. In step 502 an asymmetric cryptographic key pair is calculated. The input value could be used to generate both the public and private key, or the input value could also possibly be the private key. In step 504 the public key of the cryptographic key pair is outputted as the identifier.

In step 506, a domain parameter or a set of domain parameters are varied in accordance to a predefined scheme. Then, steps 502 to 504 are repeated using the same input value which results in a further identifier. Again, this is followed by step 506 and the cyclic performance of steps 502 to 504.

FIG. 6 shows a further embodiment of the method according to the invention as a block diagram. In step 600 an input value is accessed. In step 602 an asymmetric cryptographic key pair is calculated. In step 604 the public key of the cryptographic key pair is outputted as the identifier. In step 606 a digital signature for data which is to be deposited into a database is generated using the private key of the cryptographic key pair. In step 608 data is deposited along with the digital signature and possibly the information which of the (variations of the) domain parameter sets has been used to create the digital signature into a database using the identifier. The identifier may be used to grant access to the database or as a permission to write data into the database or it may also serve as a database access key for the data being deposited into the database. In step 610 the authenticity of the data is verified using the identifier, even though this step may alternatively performed at a later point in time. The identifier is the complementary public key to the private key considering the (variation of the) domain parameter set used to create the digital signature. The private key was used to generate the digital signature for the data and the public key can be used to verify the digital signature.

Again, steps 602 to 608 and optionally step 610 may be repeated for generation of different identifiers using a single private key, i.e. a single input value. Different datasets may be signed using the single private key, wherein the different datasets and digital signatures are then deposited into the database possibly along with the information which of the (variations of the) domain parameter sets has been used to create the digital signature using the respective identifiers. I.e., the datasets are deposited in a distributed manner in the database.

Mathematical Appendix

1. Embedding Functions.

There exist n-ary scalar functions d ₁ N× . . . ×N→N which are injective—and even bijective, where N is the set of natural numbers. The function d( ) embeds uniquely an n-dimensional space, i.e. n-tuples (k₁, . . . , k_(n)), into scalars, i.e. natural numbers k. 2. The Binary Cantor Pairing Function

The binary cantor pairing function π is an embodiment of embedding function 132. The binary cantor pairing function is defined as follows: π₁ N×N→N π(m,n)=½(m+n)(m+n+1)+n which assigns to each fraction m/n the unique natural number π (m, n)—thus demonstrating that there are no more fractions than integers. Hence, if we map both s_(T) and V_(T,i) to natural numbers and use the fact that all identities are distinct then π (s_(T), V_(T,i)) yields a unique value for each identity, even if there are equal personal secrets. To be more precise, since this function does distinguish between e.g. ½, 2/4 etc, it assigns to each fraction an infinite number of unique natural numbers. 3. Elliptic Curve Cryptography (ECC)

Let:

-   -   p be a prime number, p>3, and |F_(p) the corresponding finite         field     -   a and b integers

Then the set E of points (x, y) such that E={(x,y)ε|F _(p) ×|F _(p) |y ² =x ³ +ax+b}  (F1) defines an elliptic curve in |F_(p). (For reasons of simplicity, we skip the details on E being non-singular and, as well, we do not consider the formulae of elliptic curves over finite fields with p=2 and p=3. The subsequent statements apply to these curves, too.)

The number m of points on E is its order.

Let P,QεE be two points on E. Then the addition of points P+Q=R and RεE  (F2) can be defined in such a way that E forms an Abelian group, viz, it satisfies the rules of ordinary addition of integers. By writing P+P=[2]P

We define the k-times addition of P as [k]P, the point multiplication.

Now EC-DLP, the elliptic curve discretionary logarithm problem, states that if Q=[k]P  (F3) then with suitably chosen a, b, p and P, which are known to the public, and the as well known to the public point Q it is computationally infeasible to determine the integer k.

The order n of a point P is the order of the subgroup generated by P, i.e. the number of elements in the set {P,[2]P, . . . ,[n]P}  (F4)

With all this in mind we define an elliptic curve cryptographic (ECC) system as follows.

Let:

-   -   E be an elliptic curve of order m     -   BεE a point of E of order n, the base point

Then D={a,b,p,B,n,co(B)}  (F5) with

${{co}(B)} = \frac{m}{n}$ defines a set of domain ECC-parameters. Let now g be an integer and Q=[g]B  (F6)

Then (g, Q) is an ECC-key-pair with g being the private key and Q the public key.

For we rely on findings of Technical Guideline TR-03111, Version 1.11, issued by the Bundesamt für Sicherheit in der Informationstechnik (BSI), one of the best accredited sources for cryptographically strong elliptic curves, we can take that m=n, i.e. co(B)=1, and hence reduce (F5) to D={a,b,p,B,n}  (F7)

Now we can define our one-way function. Let D be a set of domain parameters concordant with (F7). Then f:[2,n−1]→E k

[k]B  (F8) i.e. the point multiplication (F6), is an injective one-way function. 4. Implementing Key Generator Based on ECC

The key generator 128 (cf. FIGS. 1 and 3) can be implemented using ECC.

Definitions:

-   -   There are public sets of ECC-domain parameters D₁, D₂, . . .         concordant with (F7)         D _(i) ={a _(i) ,b _(i) ,p _(i) ,B _(i) ,n _(i)}  (F9)     -   There are public functions: an embedding function d( ), a         randomizing function r( ) and our one-way function f( ) defined         by (F8).     -   There is a public set of enrolled participants (users)         T={T ₁ ,T ₂, . . . }  (F10)         -   Note that a T_(i) does not necessarily possess any             personally identifying details, i.e. we assume that T             resembles the list of participants in an anonymous             Internet-community, in which each participant can select his             name at his discretion as long as it is unique.     -   Each participant TεT chooses at his complete discretion his         personal secret s_(T). In particular, for this secret is never         revealed to anybody else—it is the participant's responsibility         to ensure this—it is not subject to any mandatory conditions,         such as uniqueness.     -   Our pseudonym derivation function is         h( )=f(r(d( )))  (F11)         -   with the following properties:     -   Given a TεT with his s_(T), a D_(i) and T, D_(i)εV_(T,i)         r(d(s _(T) ,V _(T,i)))=g _(T,i)  (F12)     -   where g_(T,i) is a unique and strong, i.e. sufficiently random,         private ECC-key for D_(i).     -   The pseudonym p_(T,i) corresponding to T, s_(T) and D_(i) is         p _(T,i) =f(g _(T,i) ,D _(i))=[g _(T,i) ]B _(i)=(x _(T,i) ,y         _(T,i))  (F13)     -   There is a public set of pseudonyms         P={p ₁ ,p ₂, . . . }  (F14)         such that P comprises one or more pseudonyms for each         participant in T computed according to (F11). This wording         implies that here is no recorded correspondence between a         participant in T and his pseudonyms in P, i.e. each p_(T,i) is         inserted in an anonymous way as p_(k) into P.         Remarks:     -   The use of multiple domain parameters enables us to endow a         single participant with a single personal secret with multiple         pseudonyms. This in turn enables a participant to be a member of         multiple pseudonymous groups such that data of these groups         cannot—for, e.g. personal or legal reasons—be correlated.         Therefore, attempts to exploit combined pseudonymous profiles         for unintended, possibly malicious purposes, are of no avail.     -   The distinction between two sets of domain parameters D_(i) and         D_(j) can be minor. In accordance with our principle to use only         accredited domain parameters, e.g. those listed in BSI TR-03111,         we can set         D _(i) ={a,b,p,B,n}  (F15)         -   by swapping B for a statistically independent B₂, i.e. by             choosing a different base point, we can set             D _(j) ={a,b,p,B ₂ ,n}  (F16)         -   For D_(i) and D_(j) refer to the same elliptic curve we can             have only one function (F12) and introduce the crucial             distinction with (F13). This vastly simplifies concrete             implementations—we select a suitable curve and vary the base             points only.

While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments.

Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. A computer program may be stored/distributed on a suitable medium, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems. Any reference signs in the claims should not be construed as limiting the scope.

LIST OF REFERENCE NUMERALS

-   -   100 Computer system     -   102 User interface     -   104 Keyboard     -   106 Sensor     -   108 Memory     -   110 Processor     -   112 User-selected secret     -   114 Combination     -   116 Private Key     -   118 Public Key     -   120 Data Object     -   122 Computer program instructions     -   126 Embedding and randomizing function     -   128 Key Generator     -   130 Database access function     -   132 Embedding function     -   134 Randomizing function     -   136 Network interface     -   138 Database     -   140 Network     -   144 Analytic system     -   146 Data Analysis Component     -   148 Random number generator     -   150 Hash function     -   152 Hash function     -   154 Database     -   156 Database     -   158 Data Object     -   190 Set of base points 

What is claimed is:
 1. A computer implemented method for performing cloud computing, the method comprising: employing cloud components, the cloud components comprising a first database and a data processing component; retrieving data from a first database by the data processing component, wherein the data is data of a first user, wherein an asymmetric cryptographic key pair comprising a public key and a private key, the data being stored pseudonymously non-encrypted in the first database with the data being assigned to an identifier, wherein the identifier comprises the public key; wherein retrieving the data from the first database comprises: receiving the identifier and retrieving the data assigned to the identifier from the first database, wherein the method further comprises processing the retrieved data to perform an analysis by the data processing component and providing a result of the analysis.
 2. The method of claim 1, wherein the cloud components further comprise a second database, wherein initially the data is only stored encrypted with the public key in the second database, wherein the method further comprises retrieving the data from the second database, decrypting it and storing the unencrypted data pseudonymously in the first database assigned to the identifier, wherein after said storage of the data in the first database the data is retrieved from the first database by the data processing component, wherein the data processing is only performed on said data retrieved from the first database.
 3. The method of claim 2, further comprising storing a result of the data processing step in the first database assigned to the identifier.
 4. The method of claim 3, further comprising retrieving the result of the data from the first database, storing said retrieved data encrypted with the public key in the second database and deleting the result of the data processing from the first database.
 5. The method of claim 2, further comprising sending the result of the data processing step to the first user with the recipient address to which the result is sent comprising the public key.
 6. The method of claim 5, wherein said result is sent encrypted with the public key to the first user.
 7. The method of claim 6, wherein said result is sent from a second user of the data processing component, wherein a second user asymmetric cryptographic key pair is associated with the second user, said key pair comprising a public sender key and a private sender key, the method further comprising generating a signature of the result using the private sender key and sending the signature to said first user as well as the second user's public key for signature verification.
 8. The method of claim 1, wherein the identifier corresponds to the public key of the first user.
 9. The method of claim 1, wherein the identifier is a pseudonym of the first user and/or wherein the identifier is an access key to the data in the first database.
 10. The method of claim 1, wherein processing the retrieved data comprises: receiving a set of rules, the set of rules describing data processing steps, analyzing the retrieved data by applying the set of rules, providing a result of the analysis.
 11. The method of claim 10, wherein the data processing component comprises an inference engine.
 12. The method according to claim 1, wherein the data is stored pseudonymously via the following method for generating a pseudonym for the user: entering a user-selected secret, storing the user-selected secret in memory, computing the private key by applying an embedding and randomizing function onto the secret, storing the private key in memory, computing the public key using the private key, the public key and the private key forming the asymmetric cryptographic key pair, erasing the secret and the private key from the memory as well as any temporary intermediate result, and outputting the public key for providing the pseudonym, wherein said pseudonym is assigned as an identity of said user and a binding between said pseudonym and said user's identity is not established by any third party.
 13. The method of claim 12, wherein the embedding and randomizing function comprises: applying a first one-way function on the secret to provide a first value, providing a random number, embedding the random number and the first value by combining them to provide a combination, applying a second one-way function on the combination to provide a second value, wherein the second value constitutes the private key.
 14. The method of claim 12, wherein the computation of the public key is performed by ECC cryptography.
 15. A non-transitory computer readable medium comprising computer executable instructions to perform the following steps on a hardware processor: employing cloud components, the cloud components comprising a first database and a data processing component; retrieving data from a first database by the data processing component, wherein the data is data of a first user, wherein an asymmetric cryptographic key pair comprising a public key and a private key, the data being stored pseudonymously non-encrypted in the first database with the data being assigned to an identifier, wherein the identifier comprises the public key; wherein retrieving the data from the first database comprises: receiving the identifier and retrieving the data assigned to the identifier from the first database, wherein the method further comprises processing the retrieved data to perform an analysis by the data processing component and providing a result of the analysis. 